Backend Engineer
About The Position
The Backend & Agent Engineer will design and develop scalable backend services and AI/agentic workflows for Medicaid Record-to-Report (R2R) processes. The role combines Python and API engineering with agent orchestration, enterprise integrations, workflow state management, observability, security, and production deployment. The ideal candidate can translate Medicaid finance workflows into secure, scalable, observable, production-ready agentic solutions. They should understand when to use deterministic business rules versus LLM-driven reasoning and ensure solutions meet high standards of security and efficiency.
Requirements
- 10+ years of experience with Python and Agentic AI.
- Strong proficiency in Python and basic SQL.
- Experience with FastAPI or an equivalent Python API framework.
- Knowledge of REST and microservices architecture.
- Understanding of Agentic AI concepts.
- Experience in agent orchestration and state management.
- Familiarity with prompt engineering and tool/function calling.
- Experience with RAG (Retrieval Augmented Generation) and EAI.
- Knowledge of workflow orchestration and exception handling.
- Experience with automation testing and CI/CD practices.
- Understanding of observability, logging, telemetry, and tracing.
- Knowledge of IAM/RBAC, secrets management, encryption, and secure API design.
Nice To Haves
- Experience with Azure OpenAI.
- Knowledge of Databricks.
- Experience with MLflow tracing and evaluation.
- Familiarity with Unity3D.
- Understanding of MCP (Model Context Protocol).
- Experience with Databricks and Model Serving.
- Familiarity with Microsoft Azure DevOps or GitHub Actions.
- Experience with Docker containers.
Responsibilities
- Develop scalable Python backend services, REST APIs, and integration components.
- Build and orchestrate AI agents for reconciliation, exception investigation, variance analysis, and close processes.
- Implement agent state management, routing, tool/function calling, retries, checkpoints, and failure recovery.
- Integrate agents with enterprise data, SQL, APIs, rules engines, and governed tools.
- Implement human-in-the-loop review and approval workflows.
- Develop prompts, grounded context, structured outputs, and evidence-backed agent responses.
- Build automated unit, API, integration, regression, and agent-evaluation tests.
- Implement logging, tracing, monitoring, security, and production-readiness controls.
- Support CI/CD, deployment, configuration, and operational troubleshooting.
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What This Job Offers
Career Level
Senior
Education Level
No Education Listed
